Thermally driven flows and urban heat island interactions in Madrid: a multi-scale analysis.

Madrid is located in a topographically complex environment influenced by the Guadarrama mountain range, where thermally-driven flows (TDFs), such as mountain–valley breezes, interact with the urban heat island (UHI) and modulate local meteorological conditions. Despite the well-documented warming associated with increasing urbanisation, the coupling between TDFs and the UHI remains insufficiently characterised.

Long-term observational datasets (1961–2023) from urban and rural meteorological stations reveal significant warming trends, more pronounced in summer than in winter, together with marked differences between maximum and minimum temperatures. The UHI intensity, defined from minimum temperature differences, shows mean values close to 2 °C (depending on the rural reference station), and exhibits a strong dependence on synoptic conditions, reaching up to ~3.3 °C under stable situations, which are, indeed, ideal conditions for TDF development.

The variability of TDFs is analyzed using both long-term observations and specific field campaigns, focusing on the diurnal and seasonal cycles as well as their frequency, intensity and directional patterns. These circulations play a key role in urban ventilation, air quality, and boundary layer structure, with significant implications for thermal comfort and population vulnerability.

The interaction between TDFs and the UHI is further examined through mesoscale simulations using the Weather Research and Forecasting (WRF) model with the BEP-BEM urban canopy scheme (Carbone et al., 2024; Salamanca et al., 2010; Martilli et al., 2002). The results highlight a two-way coupling: urban-induced thermal anomalies modify local circulations, while TDFs influence the intensity and spatial distribution of the UHI.

These findings provide new insights and an integrated view of the interactions between urbanization, topography, and atmospheric dynamics in complex environments, contributing to the improvement of urban representation in numerical models and supporting the development of climate adaptation strategies.